Kate joined the faculty in the Department of Statistics at The Ohio State University in 2003. She served as an associate director of the Mathematical Biosciences Institute (MBI) from 2015-2017, before assuming the role of MBI co-director in 2018. She is a faculty affiliate of the Institute for Population Research, the Criminal Justice Research Institute, and the Translational Data Analytics Institute at Ohio State. She is currently an associate editor for the Annals of Applied Statistics and Bayesian Analysis and has served the statistics profession through various elected roles in sections of the American Statistical Association (ASA) and in the International Society for Bayesian Analysis. She received the ASA Section on Statistics and the Environment’s 2013 Young Investigator Award and was elected Fellow of the ASA in 2014.
Calder’s research focuses on the development of stochastic models for phenomena that exhibit complex dependencies, particularly when the dependencies are spatial and/or temporal in nature. Her methodological contributions have been in the areas of dimension reduction for spatio-temporal data, the development of covariate-driven nonstationary spatial models, data-augmentation algorithms for Bayesian spatial generalized linear (mixed) models, latent space models for two-mode networks, and model-based comparisons of networks. Much of her research is motivated by applications in the environmental, social, and health sciences. She has received funding for her research from the NIH, NSF, NASA, and other agencies and foundations.
Calder holds a BA in Mathematics from Northwestern University and an MS and PhD in Statistics from Duke University.